Innovation in Language Learning

As Artificial Intelligence (AI) technologies become increasingly integrated in language education, questions around ethical and responsible implementation are gaining more attention. Yet, innovation in this domain often advances without sufficient attention to critical ethical concerns (1) such as teacher agency (2), learner agency (3), and cultural sensitivity (4). This presentation introduces a conceptual framework for ethical AI integration in language education, comprising bias mitigation, privacy and data protection, and human-AI collaboration. This three-pillar framework provides a foundation for teachers, institutions, and developers to navigate complex ethical perspectives. It identifies critical ethical concerns such as learner autonomy, fairness, algorithmic bias, transparency, data privacy, teacher displacement, the digital divide, teacher agency as well as the ethical challenge of AI-generated materials failing to reflect learners' cultural and linguistic identities. Also, this presentation is grounded in the presenter’s ongoing doctoral research project that aims to build a comprehensive ethical framework for AI-enhanced language education. In particular, the framework highlights the importance of designing AI-enhanced learning environments that promote inclusivity and empower both learners and teachers. By positing ethics not as a barrier but as a driver of innovation, this presentation calls for a more reflective, context-sensitive, and human-centered approach to the future of language education.